For the shortcomings of current 3D reconstruction models such as poor reconstruction effect and blurred edges when dealing with weakly textured and textureless objects, this paper fuses the rich polarization spectral information with multi-view 3D reconstruction and presents the MP-mip-NeRf 360 model. This paper has constructed a multi-angle polarization dataset and systematic theoretical model validations are completed on this dataset. Compared with existing deep learning models, our model achieves better results in terms of accuracy, rendering more realistic scenes and obtaining more detailed depth maps.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Multi-view 3D Reconstruction by Fusing Polarization Information

  • Gaomei Hu,
  • Haimeng Zhao,
  • Qirun Huo,
  • Jianfang Zhu,
  • Peng Yang

摘要

For the shortcomings of current 3D reconstruction models such as poor reconstruction effect and blurred edges when dealing with weakly textured and textureless objects, this paper fuses the rich polarization spectral information with multi-view 3D reconstruction and presents the MP-mip-NeRf 360 model. This paper has constructed a multi-angle polarization dataset and systematic theoretical model validations are completed on this dataset. Compared with existing deep learning models, our model achieves better results in terms of accuracy, rendering more realistic scenes and obtaining more detailed depth maps.